The Firewall Rule That Was ‘Low-Risk’ Until It Took Down 7 Business Services
The change ticket was six lines long. One CI. One affected network segment. Zero downstream services. Management pre-approved it as …
Inherited CMDB Data Quality: 63% Degraded on Day 1
Inherited CMDB data quality degrades faster than manual teams can correct it. A discovery-sourced audit of a 14,000-CI CMDB found …
AI on a Stale CMDB: A CIO’s Honest Account
Deploying AI on a stale CMDB produces confidently wrong recommendations — not random errors, but systematically incorrect outputs that trace …
What ‘AI-Ready IT Data’ Actually Means: The 5-Point Checklist Before Automation
An AI-ready IT data checklist is a five-point assessment that measures whether enterprise CMDB data can reliably support agentic AI …
The AI Pilot Was Delayed 4 Months Because Nobody Had Audited the CMDB First. A Post-Mortem.
An AI change risk automation pilot post-mortem is a structured review of why a data-dependent automation program paused or failed …
Why AI Initiatives in IT Stall on Data Quality — Not Model Choice
AI initiative failure in IT operations is a data quality problem, not a model quality problem. When AI projects for …
Inherited CMDB Data Quality: 63% Degraded on Day 1
Inherited CMDB data quality degrades faster than manual teams can correct it. A discovery-sourced audit of a 14,000-CI CMDB found …
Change Impact Analysis False Negative: Why Zero Risk Isn’t Always Safe
A change impact analysis false negative occurs when the analysis correctly reflects the CMDB — and the CMDB is incomplete. …
CMDB Dependency Gap: What Change Impact Analysis Can’t See
The CMDB dependency gap is the difference between the CI relationships your CMDB documents and those that actually exist in …
